In this paper, a deformable object is considered for camera network deployment with the aim of visual coverage. The object contour is discretized into sampled points as meshes, and the deformation is represented by co...
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In this paper, a deformable object is considered for camera network deployment with the aim of visual coverage. The object contour is discretized into sampled points as meshes, and the deformation is represented by continuous trajectories for the sampled points. To reduce the computational complexity, some feature points are carefully selected to represent the continuous deformation process. The visual coverage for the deformable object is transferred to cover the specific feature points. In particular, the vertexes of a rectangle that encloses the entire deformation trajectory of every sampled point on the object contour are chosen as the feature points. An improved wolf pack algorithm is then proposed to solve the optimization problem. Finally, both simulation and experimental results are given to demonstrate the effectiveness of the proposed deployment method of camera network.
Aiming at the key optimization problems of wireless sensor networks in complex industrial application environments, such as the optimum coverage and the reliability of the network, a novel topology optimization of cov...
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Aiming at the key optimization problems of wireless sensor networks in complex industrial application environments, such as the optimum coverage and the reliability of the network, a novel topology optimization of coverage-oriented strategy for wireless sensor networks based on the wolf pack algorithm is proposed. Combining the characteristics of topology structure of wireless sensor networks and the optimization idea of the wolf pack algorithm redefines the group's wandering and surprise behavior. A novel head wolf mutation strategy is proposed, which increases the neighborhood search range of the optimal solution, enhances the uniformity of wolfpack distribution and the ergodicity ability of the wolfpack search, and greatly improves the calculation speed and the accuracy of the wolf pack algorithm. With the same probability, the cluster heads are randomly selected periodically, and the overall energy consumption of wireless sensor networks is evenly distributed to the sensor node to realize the balanced distribution of the data of the member nodes in the cluster and complete the design of the topology optimization of wireless sensor networks. Through algorithm simulation and result analysis, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the wolf swarm algorithm shows its advantages in terms of the residual energy of the sensor node, the average transmission delay, the average packet delivery rate, and the coverage of the network. Among them, compared with the particle swarm optimization algorithm and artificial fish swarm algorithm, the remaining energy of nodes has increased by 9.5% and 15.5% and the average coverage of the network has increased by 10.5% and 5.6%, respectively.
The proton exchange membrane (PEM) is one of the significant components in PEM fuel cells. However, conventional synthesis experiments for proton exchange membrane (PEM) require considerable workload and time due to c...
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The proton exchange membrane (PEM) is one of the significant components in PEM fuel cells. However, conventional synthesis experiments for proton exchange membrane (PEM) require considerable workload and time due to complicated conditions and various influencing factors. Here we initially utilized artificial intelligence (AI) techniques based on the artificial wolf pack algorithm (AWPA) to optimize the synthesis reaction conditions of the ring-opening metathesis polymerization (ROMP) reaction of norbornene derivatives for PEM preparation. An empirical model was established based on four variables, including temperature, reaction time, catalyst amount and ratio of reactants, with two fitness functions, including molecular weight (MW) and molecular weight distribution (MWD). Four trend indices were used, including the mean average precision (mAP), the mean, standard deviation (mSTD), the moving mean of the average precision (mmAP) and the moving mean of standard derivation (mmSD). The theoretical optimum values of operating conditions were obtained successfully, including reactant ratio (0.71), temperature (41.23 degrees C), catalyst content (0.20) and reaction time (47.94 min). The method in this paper helps optimize PEM preparation conditions and guides a database for AI-aid ROMP reactions.
More and more marine debris not only damages the environment, but also endangers human health and marine life. Since the location of marine debris is not fixed, we first apply the GNOME software to predict the traject...
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More and more marine debris not only damages the environment, but also endangers human health and marine life. Since the location of marine debris is not fixed, we first apply the GNOME software to predict the trajectory of marine debris and determine its location. Then, the logistics network is used to optimize the collection of marine debris. A mixed integer linear programming model for debris vessel routing is proposed. The objective function is to minimize the total cost, which includes the fuel cost consisting of is a piecewise linear function, labor cost, and fixed cost consisting of rent and insurance relative to the vessels used, taking into account the vessel weight capacity, fuel tank capacity, and time windows constraint at each debris location. We propose a hybrid algorithm of adaptive large-scale neighborhood search, combined with a wolf pack algorithm. This paper takes Yangtze River Estuary to the East China Sea as an example to verify the proposed model and algorithm. The results show that, compared with the worst-case, the most appropriate collection time can save up to 6.38% of the cost, which is about $75,590 per calendar year. The sensitivity analysis of debris weight and vessel capacity is also performed.
In mining subsidence monitoring, "discrete point deformation monitoring and mining subsidence prediction model" is often used. The key to mining subsidence monitoring is to choose a convenient, economical, a...
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In mining subsidence monitoring, "discrete point deformation monitoring and mining subsidence prediction model" is often used. The key to mining subsidence monitoring is to choose a convenient, economical, accurate, and reliable deformation monitoring method. In this study, the terrestrial laser scanner (TLS) with convenient, high efficiency, and high precision was used as the data acquisition method. And the Boltzmann function prediction method-exponent Knothe time function mining subsidence prediction model with high simulation degree for the deformation of rock strata above the mining affected area was constructed to calculate the surface deformation. Taking the surrounding area of South 1312 (1) working face of Gubei Coal Mine in Huainan, China as the application area, first, the model parameters are obtained by the wolf pack algorithm according to the TLS scanning point cloud data, followed by predicting the subsidence and horizontal displacement of the surrounding area. Finally, the building mining damage assessment is conducted according to the deformation of the surrounding area of the working face. The analysis results show that the mining subsidence monitoring method proposed in this paper can obtain the surface deformation in a large area affected by mining after observing a small area. The surface deformation obtained by this method is consistent with the surface deformation obtained by leveling observation. Moreover, the predicted effect of this method is better than that of the mining subsidence monitoring method using PIM-KTF model combined with TLS, and it has certain robustness to the geological and mining condition errors. The results of this work can provide a reference for predicting mining subsidence influence scope, deformation size, and mining damage assessment of mining buildings.
This work uses an intelligent algorithm named the wolf pack algorithm (WPA) in the design of multiple pairs of square Helmholtz coil structures to generate highly uniform magnetic fields within a limited volume for ex...
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This work uses an intelligent algorithm named the wolf pack algorithm (WPA) in the design of multiple pairs of square Helmholtz coil structures to generate highly uniform magnetic fields within a limited volume for external magnetic shielding of magnetometers. Square Helmholtz coils are widely used in magnetic shielding, magnetic navigation, and aerospace applications, among others. The coil structure is simple, and the generated magnetic field is convenient to calculate. Simultaneously, we set the appropriate penalty function and boundary conditions as well as add the necessary design parameters to achieve the final design. Compared with the traditional design, this method solves the problem of coil assembly to generate a highly uniform magnetic field under various structural and process constraints. The results show that the uniformity of multiple pairs of coils is better than that of a single pair for the same volume and the uniformity of the coil designed by the WPA is better than that designed by the PSO. The measured results of the device are nearly consistent with the theoretical values. (c) 2021 Elsevier B.V. All rights reserved.
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